Cleaning scripts:

Load data:

Exclude random responses

d_overall_means = d %>%
  group_by(modal, workerid) %>% 
  summarise(rating_m_overall = mean(rating))

d_indiv_means =  d %>%
  group_by(modal,percent_middle, workerid) %>% 
  summarise(rating_m = mean(rating))

d_indiv_merged = merge(d_indiv_means, d_overall_means, by=c("workerid", "modal"))

cors = d_indiv_merged %>%
  group_by(workerid) %>%
  summarise(corr = cor(rating_m, rating_m_overall))

exclude = cors %>%
  filter(corr > 0.75) %>%
  .$workerid

print(paste("Excluded", length(exclude), "participants based on random responses."))
## [1] "Excluded 13 participants based on random responses."
d = d %>% filter(!(workerid %in% exclude))

Aggregated results

## Individual plots

plot(ps1$by_participant)

AUC Computation

## 
##  Two Sample t-test
## 
## data:  aucs.positive$auc_diff and aucs.negative$auc_diff
## t = 0.24409, df = 132, p-value = 0.8075
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -6.824517  8.745797
## sample estimates:
##   mean of x   mean of y 
## -0.01512868 -0.97576872